Why is the State of Neural Network Pruning so Confusing? On the
Fairness, Comparison Setup, and Trainability in Network Pruning

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Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning

12 January 2023

Huan Wang

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Papers citing "Why is the State of Neural Network Pruning so Confusing? On the Fairness, Comparison Setup, and Trainability in Network Pruning"

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Title
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,426 0 10 Dec 2015
Data-dependent Initializations of Convolutional Neural Networks Philipp Krahenbuhl Carl Doersch Jeff Donahue Trevor Darrell VLM 93 203 0 21 Nov 2015
All you need is a good init Dmytro Mishkin Jirí Matas ODL 94 612 0 19 Nov 2015
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 263 8,859 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 313 6,700 0 08 Jun 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 338 18,651 0 06 Feb 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,508 0 04 Sep 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 280 14,713 0 20 Jun 2014
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 246 16,377 0 30 Apr 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 183 1,852 0 20 Dec 2013